Literature DB >> 22903520

Predatory fish select for coordinated collective motion in virtual prey.

C C Ioannou1, V Guttal, I D Couzin.   

Abstract

Movement in animal groups is highly varied and ranges from seemingly disordered motion in swarms to coordinated aligned motion in flocks and schools. These social interactions are often thought to reduce risk from predators, despite a lack of direct evidence. We investigated risk-related selection for collective motion by allowing real predators (bluegill sunfish) to hunt mobile virtual prey. By fusing simulated and real animal behavior, we isolated predator effects while controlling for confounding factors. Prey with a tendency to be attracted toward, and to align direction of travel with, near neighbors tended to form mobile coordinated groups and were rarely attacked. These results demonstrate that collective motion could evolve as a response to predation, without prey being able to detect and respond to predators.

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Year:  2012        PMID: 22903520     DOI: 10.1126/science.1218919

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  83 in total

1.  The evolution of antipredator behaviour following relaxed and reversed selection in Alaskan threespine stickleback fish.

Authors:  Matthew A Wund; John A Baker; Justin L Golub; Susan A Foster
Journal:  Anim Behav       Date:  2015-08-01       Impact factor: 2.844

2.  Predator confusion is sufficient to evolve swarming behaviour.

Authors:  Randal S Olson; Arend Hintze; Fred C Dyer; David B Knoester; Christoph Adami
Journal:  J R Soc Interface       Date:  2013-06-05       Impact factor: 4.118

3.  Collective response to perturbations in a data-driven fish school model.

Authors:  Daniel S Calovi; Ugo Lopez; Paul Schuhmacher; Hugues Chaté; Clément Sire; Guy Theraulaz
Journal:  J R Soc Interface       Date:  2015-03-06       Impact factor: 4.118

4.  Predators attacking virtual prey reveal the costs and benefits of leadership.

Authors:  Christos C Ioannou; Florence Rocque; James E Herbert-Read; Callum Duffield; Josh A Firth
Journal:  Proc Natl Acad Sci U S A       Date:  2019-04-15       Impact factor: 11.205

5.  Collective learning from individual experiences and information transfer during group foraging.

Authors:  Andrea Falcón-Cortés; Denis Boyer; Gabriel Ramos-Fernández
Journal:  J R Soc Interface       Date:  2019-02-28       Impact factor: 4.118

6.  An agent-based approach for modelling collective dynamics in animal groups distinguishing individual speed and orientation.

Authors:  Sara Bernardi; Marco Scianna
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-07-27       Impact factor: 6.237

7.  Both information and social cohesion determine collective decisions in animal groups.

Authors:  Noam Miller; Simon Garnier; Andrew T Hartnett; Iain D Couzin
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-25       Impact factor: 11.205

8.  A unifying framework for quantifying the nature of animal interactions.

Authors:  Jonathan R Potts; Karl Mokross; Mark A Lewis
Journal:  J R Soc Interface       Date:  2014-07-06       Impact factor: 4.118

9.  Decision accuracy in complex environments is often maximized by small group sizes.

Authors:  Albert B Kao; Iain D Couzin
Journal:  Proc Biol Sci       Date:  2014-04-23       Impact factor: 5.349

Review 10.  Loneliness across phylogeny and a call for comparative studies and animal models.

Authors:  John T Cacioppo; Stephanie Cacioppo; Steven W Cole; John P Capitanio; Luc Goossens; Dorret I Boomsma
Journal:  Perspect Psychol Sci       Date:  2015-03
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